Computational thinking is a means to understand and solve complex problems through using computer science concepts and techniques. While there is an increase in the number of initiatives focusing on coding, whether they (a) address computational thinking and problem-solving skills and (b) use methods of teaching problem solving is yet to be…

Recent research has emphasized the importance of leveraging embodied interactions for learning critical STEM concepts. ELASTIC3S--an embodied environment for learning about cross-cutting concepts (i.e., non-linear growth)--allows learners to interact with different science simulations through whole-body gestures. Technological advances in gesture…

Problem-based learning (PBL) and early clinical placements (CP) are recognised as complementary strategies for developing clinical reasoning (CR) in medical education. However, how alternating between these formats influences the CR process from students' perspectives remains underexplored. This qualitative-led exploratory mixed-methods study…

The prevalence of unfounded beliefs (e.g., supernatural or conspiracy beliefs) remains an important issue due to their negative consequences in various domains. Interventions were shown to reduce supernatural beliefs only when addressing pseudoscientific ones. Based on these findings, we designed a single session intervention aiming to teach…

This research proposes the integration of robotic education and scenario-based learning (SBL) paradigm for teaching computational thinking (CT) to enhance the computational abilities of primary school students, based on digital innovation and a teaching assistant robot acceptance model. The sample group consisted of 532 primary school teachers and…

This study explores the effectiveness of four-word frame training in enhancing the reading comprehension and contextual word-guessing skills of Thai public health students studying English as a Foreign Language. A mixed-methods approach was employed with 22 fourth-year undergraduate students, combining quantitative pre- and post-test assessments…

This research proposes a methodological approach to using the social network Instagram® as a tool for collaborative e-learning activities in higher education. Collaborative e-learning activities are conducted on Instagram® through challenges and quizzes. The main aim of these activities is to encourage students' creativity, motivation for…

While the effects of pattern learning on language processing are well known, the way in which pattern learning shapes exploratory behavior has long gone unnoticed. We report on the way in which individual differences in statistical pattern learning affect performance in the domain of language along multiple dimensions. Analyzing data from healthy…

This study examined the effectiveness of a Derived Relational Responding (DRR) program in improving reading comprehension accuracy among upper elementary students without intellectual or developmental disabilities who struggle to meet grade-level reading standards. Addressing a gap in current interventions, the study investigated whether DRR,…

Children are very curious about the world around them. You may find them peering at tadpoles in a pond, counting ants on a log, or wondering about the stars, the sun, and the moon. I have been asked many times: Is the moon really made of cheese? Do astronauts live on the moon? Why does the moon look different every time I look up? Introducing…

The large rates of students' failure is a very frequent problem in undergraduate courses, being even more evident in exact sciences. Pointing out the reasons of such problem is a paramount research topic, though not an easy task. An alternative is to use Educational Data Mining techniques (EDM), which enables one to convert data from educational…

Demographic features are commonly used in Educational Data Mining (EDM) research to predict at-risk students. Yet, the practice of using demographic features has to be considered extremely problematic due to the data's sensitive nature, but also because (historic and representation) biases likely exist in the training data, which leads to strong…

Over the past fifty years, extensive research has examined the influence of causal attributions on cognitions, emotions, and behaviours in educational contexts. However, these studies often relied on inferences about dimensional properties of attributions, and not on students' perceptions of them. This study innovates by directly assessing these…

The digital era has significantly reshaped journalism, emphasizing the pivotal role of data-driven reporting. This review delves into the nexus of data journalism and journalism education, investigating dominant study characteristics, challenges, and gaps for future research. Examining 41 relevant articles through the Arksey and O'Malley…

This article introduces researchers in the science concerned with developing and studying research methods, measurement, and evaluation (RMME) to the educational data mining (EDM) community. It assumes that the audience is familiar with traditional priorities of statistical analyses, such as accurately estimating model parameters and inferences…